Stationarity analysis of the stock market data and its application to mechanical trading

Kazuki Kanehira and Norikazu Todoroki

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Abstract: This study proposes a scheme for stationarity analysis of stock price fluctuations based on KM$_2$O-Langevin theory. Using this scheme, we classify the time-series data of stock price fluctuations into three periods: stationary, non-stationary, and intermediate. We then suggest an example of a low-risk stock trading strategy to demonstrate the usefulness of our scheme by using actual stock index data. Our strategy uses a trend-based indicator, moving averages, for stationary periods and an oscillator-based indicator, psychological lines, for non-stationary periods to make trading decisions. Finally, we confirm that our strategy is a safe trading strategy with small maximum drawdown by back testing on the Nikkei Stock Average. Our study, the first to apply the stationarity analysis of KM$_2$O-Langevin theory to actual mechanical trading, opens up new avenues for stock price prediction.

Date: 2021-12, Revised 2022-02
New Economics Papers: this item is included in nep-cwa, nep-ets and nep-fmk
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2112.12459

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